# CUDA Graphs

Published articles for CUDA Graphs.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## High-Throughput Structure Prediction with BioNeMo Inference Runtime

DevFeed: [High-Throughput Structure Prediction with BioNeMo Inference Runtime](<https://devfeed.tech/articles/high-throughput-structure-prediction-with-bionemo-inference-runtime-6836.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/high-throughput-structure-prediction-with-bionemo-inference-runtime/>)

Author: Elizabeth Goodman

Published: 2026-09-10T15:00:00Z

Content type: tutorial

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [AI, ML & Data Engineering](<https://devfeed.tech/topics/ai-ml-data-engineering.md>)

Tags: [bionemo](<https://devfeed.tech/tags/bionemo.md>), [cuda](<https://devfeed.tech/tags/cuda.md>), [cuda-graphs](<https://devfeed.tech/tags/cuda-graphs.md>), [data-center-cloud](<https://devfeed.tech/tags/data-center-cloud.md>), [data-science](<https://devfeed.tech/tags/data-science.md>), [drug-discovery](<https://devfeed.tech/tags/drug-discovery.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [healthcare-life-sciences](<https://devfeed.tech/tags/healthcare-life-sciences.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [hpc-scientific-computing](<https://devfeed.tech/tags/hpc-scientific-computing.md>), [inference](<https://devfeed.tech/tags/inference.md>), [integration](<https://devfeed.tech/tags/integration.md>), [kernels](<https://devfeed.tech/tags/kernels.md>), [model](<https://devfeed.tech/tags/model.md>), [models](<https://devfeed.tech/tags/models.md>), [node](<https://devfeed.tech/tags/node.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [python](<https://devfeed.tech/tags/python.md>), [pytorch](<https://devfeed.tech/tags/pytorch.md>), [resource](<https://devfeed.tech/tags/resource.md>), [scale](<https://devfeed.tech/tags/scale.md>), [simulation-modeling-design](<https://devfeed.tech/tags/simulation-modeling-design.md>), [tokenization](<https://devfeed.tech/tags/tokenization.md>), [torch](<https://devfeed.tech/tags/torch.md>), [tutorial](<https://devfeed.tech/tags/tutorial.md>), [workflow](<https://devfeed.tech/tags/workflow.md>)

### AI overview

A tutorial on using NVIDIA BioNeMo Inference Runtime to accelerate biomolecular structure-prediction models on GPUs. It covers the end-to-end Boltz2 workflow, PyTorch integration, input requirements, and Ray-based single-node throughput scaling.

### Source excerpt

Biomolecular structure prediction is now often run at proteome scale, where the goal is to move an entire worklist through the pipeline efficiently. NVIDIA...

## Kernel Fusion in NVIDIA CUDA: Optimizing Memory Traffic and Launch Overhead

DevFeed: [Kernel Fusion in NVIDIA CUDA: Optimizing Memory Traffic and Launch Overhead](<https://devfeed.tech/articles/kernel-fusion-in-nvidia-cuda-optimizing-memory-traffic-and-launch-overhead-6873.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/kernel-fusion-in-nvidia-cuda-optimizing-memory-traffic-and-launch-overhead/>)

Author: Michelle Horton

Published: 2026-07-10T16:41:03Z

Content type: tutorial

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [GPU](<https://devfeed.tech/topics/gpu.md>), [C++](<https://devfeed.tech/topics/c-plus-plus.md>)

Tags: [c-plus-plus](<https://devfeed.tech/tags/c-plus-plus.md>), [cuda](<https://devfeed.tech/tags/cuda.md>), [cuda-graphs](<https://devfeed.tech/tags/cuda-graphs.md>), [developer-tools-techniques](<https://devfeed.tech/tags/developer-tools-techniques.md>), [featured](<https://devfeed.tech/tags/featured.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [kernel](<https://devfeed.tech/tags/kernel.md>), [launch](<https://devfeed.tech/tags/launch.md>), [memory](<https://devfeed.tech/tags/memory.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [performance](<https://devfeed.tech/tags/performance.md>)

### AI overview

This tutorial explains CUDA kernel fusion for GPU optimization. Combining operations into one kernel keeps intermediate values in registers, reduces global-memory traffic, and avoids separate kernel launches; it also distinguishes this approach from CUDA Graphs.

### Source excerpt

There are many ways to optimize code for GPUs. In this post, you'll learn how kernel fusion can improve memory bandwidth and reduce kernel launch overhead,...